Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations2966
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory278.1 KiB
Average record size in memory96.0 B

Variable types

Numeric11

Alerts

avg_basket_size is highly overall correlated with gros_revenueHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 2 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gros_revenue is highly overall correlated with avg_basket_size and 2 other fieldsHigh correlation
invoice_no is highly overall correlated with avg_unique_basket_size and 2 other fieldsHigh correlation
quantity is highly overall correlated with avg_unique_basket_size and 2 other fieldsHigh correlation
avg_ticket is highly skewed (γ1 = 53.41722918) Skewed
qtd_returns is highly skewed (γ1 = 51.77236982) Skewed
avg_basket_size is highly skewed (γ1 = 44.65585181) Skewed
customer_id has unique values Unique
recence_days has 34 (1.1%) zeros Zeros
qtd_returns has 1480 (49.9%) zeros Zeros

Reproduction

Analysis started2025-06-11 09:15:03.146329
Analysis finished2025-06-11 09:15:15.387418
Duration12.24 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2966
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.646
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:15.460324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.25
Q113799.75
median15220.5
Q316769.5
95-th percentile17964.75
Maximum18287
Range5940
Interquartile range (IQR)2969.75

Descriptive statistics

Standard deviation1719.3683
Coefficient of variation (CV)0.11259302
Kurtosis-1.2062852
Mean15270.646
Median Absolute Deviation (MAD)1487
Skewness0.031911548
Sum45292737
Variance2956227.2
MonotonicityNot monotonic
2025-06-11T06:15:15.574568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12558 1
 
< 0.1%
17850 1
 
< 0.1%
13047 1
 
< 0.1%
12583 1
 
< 0.1%
13748 1
 
< 0.1%
15100 1
 
< 0.1%
16956 1
 
< 0.1%
17010 1
 
< 0.1%
15274 1
 
< 0.1%
18139 1
 
< 0.1%
Other values (2956) 2956
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gros_revenue
Real number (ℝ)

High correlation 

Distinct2951
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.4101
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:15.682379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile230.9525
Q1571.02
median1085.51
Q32310.295
95-th percentile7226.025
Maximum279138.02
Range279131.82
Interquartile range (IQR)1739.275

Descriptive statistics

Standard deviation10565.121
Coefficient of variation (CV)3.8426864
Kurtosis355.16801
Mean2749.4101
Median Absolute Deviation (MAD)672.255
Skewness16.794993
Sum8154750.4
Variance1.1162178 × 108
MonotonicityNot monotonic
2025-06-11T06:15:16.060634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
889.93 2
 
0.1%
2053.02 2
 
0.1%
745.06 2
 
0.1%
379.65 2
 
0.1%
2092.32 2
 
0.1%
731.9 2
 
0.1%
1314.45 2
 
0.1%
331 2
 
0.1%
533.33 2
 
0.1%
1353.74 2
 
0.1%
Other values (2941) 2946
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
70.02 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
136263.72 1
< 0.1%
124564.53 1
< 0.1%
116725.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recence_days
Real number (ℝ)

Zeros 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.193864
Minimum0
Maximum373
Zeros34
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:16.169950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.574055
Coefficient of variation (CV)1.2084341
Kurtosis2.7617558
Mean64.193864
Median Absolute Deviation (MAD)26
Skewness1.7950238
Sum190399
Variance6017.7341
MonotonicityNot monotonic
2025-06-11T06:15:16.284781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
3 85
 
2.9%
2 84
 
2.8%
8 76
 
2.6%
10 67
 
2.3%
7 66
 
2.2%
9 66
 
2.2%
17 64
 
2.2%
22 55
 
1.9%
Other values (262) 2217
74.7%
ValueCountFrequency (%)
0 34
 
1.1%
1 99
3.3%
2 84
2.8%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 3
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

invoice_no
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.75084
Minimum1
Maximum7837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:16.409958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7837
Range7836
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.35616
Coefficient of variation (CV)2.1943325
Kurtosis354.16902
Mean122.75084
Median Absolute Deviation (MAD)44
Skewness15.673325
Sum364079
Variance72552.743
MonotonicityNot monotonic
2025-06-11T06:15:16.546113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 46
 
1.6%
20 38
 
1.3%
35 35
 
1.2%
15 33
 
1.1%
19 32
 
1.1%
11 32
 
1.1%
29 32
 
1.1%
25 30
 
1.0%
18 30
 
1.0%
27 30
 
1.0%
Other values (458) 2628
88.6%
ValueCountFrequency (%)
1 5
 
0.2%
2 14
0.5%
3 16
0.5%
4 17
0.6%
5 26
0.9%
6 28
0.9%
7 18
0.6%
8 19
0.6%
9 27
0.9%
10 27
0.9%
ValueCountFrequency (%)
7837 1
< 0.1%
5586 1
< 0.1%
5095 1
< 0.1%
4577 1
< 0.1%
2697 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1672 1
< 0.1%
1636 1
< 0.1%

quantity
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.75084
Minimum1
Maximum7837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:16.661911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7837
Range7836
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.35616
Coefficient of variation (CV)2.1943325
Kurtosis354.16902
Mean122.75084
Median Absolute Deviation (MAD)44
Skewness15.673325
Sum364079
Variance72552.743
MonotonicityNot monotonic
2025-06-11T06:15:16.781134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 46
 
1.6%
20 38
 
1.3%
35 35
 
1.2%
15 33
 
1.1%
19 32
 
1.1%
11 32
 
1.1%
29 32
 
1.1%
25 30
 
1.0%
18 30
 
1.0%
27 30
 
1.0%
Other values (458) 2628
88.6%
ValueCountFrequency (%)
1 5
 
0.2%
2 14
0.5%
3 16
0.5%
4 17
0.6%
5 26
0.9%
6 28
0.9%
7 18
0.6%
8 19
0.6%
9 27
0.9%
10 27
0.9%
ValueCountFrequency (%)
7837 1
< 0.1%
5586 1
< 0.1%
5095 1
< 0.1%
4577 1
< 0.1%
2697 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1672 1
< 0.1%
1636 1
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct2964
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.931584
Minimum2.1505882
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:16.894001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.9143418
Q113.119823
median17.946876
Q324.986122
95-th percentile90.50125
Maximum56157.5
Range56155.349
Interquartile range (IQR)11.866299

Descriptive statistics

Standard deviation1037.4583
Coefficient of variation (CV)19.977406
Kurtosis2887.7872
Mean51.931584
Median Absolute Deviation (MAD)5.9750522
Skewness53.417229
Sum154029.08
Variance1076319.8
MonotonicityNot monotonic
2025-06-11T06:15:17.007217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.47833333 2
 
0.1%
4.162 2
 
0.1%
12.67938776 1
 
< 0.1%
3.411945289 1
 
< 0.1%
16.29372093 1
 
< 0.1%
36.24411765 1
 
< 0.1%
29.78416667 1
 
< 0.1%
22.8792623 1
 
< 0.1%
20.51104167 1
 
< 0.1%
149.025 1
 
< 0.1%
Other values (2954) 2954
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.381858
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:17.119811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q126
median48.392857
Q385.333333
95-th percentile201
Maximum366
Range365
Interquartile range (IQR)59.333333

Descriptive statistics

Standard deviation63.559053
Coefficient of variation (CV)0.94326656
Kurtosis4.8832458
Mean67.381858
Median Absolute Deviation (MAD)26.27381
Skewness2.0624282
Sum199854.59
Variance4039.7532
MonotonicityNot monotonic
2025-06-11T06:15:17.234768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 25
 
0.8%
4 21
 
0.7%
70 21
 
0.7%
7 20
 
0.7%
49 18
 
0.6%
35 18
 
0.6%
46 17
 
0.6%
11 17
 
0.6%
21 17
 
0.6%
28 16
 
0.5%
Other values (1248) 2776
93.6%
ValueCountFrequency (%)
1 16
0.5%
1.5 1
 
< 0.1%
2 13
0.4%
2.5 1
 
< 0.1%
2.601398601 1
 
< 0.1%
3 15
0.5%
3.321428571 1
 
< 0.1%
3.330357143 1
 
< 0.1%
3.5 2
 
0.1%
4 21
0.7%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
363 1
 
< 0.1%
362 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

High correlation 

Distinct1348
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.063159198
Minimum0.0054495913
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:17.349016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0094339623
Q10.017777778
median0.029296366
Q30.055319294
95-th percentile0.22222222
Maximum3
Range2.9945504
Interquartile range (IQR)0.037541516

Descriptive statistics

Standard deviation0.13440044
Coefficient of variation (CV)2.1279631
Kurtosis122.00234
Mean0.063159198
Median Absolute Deviation (MAD)0.014270062
Skewness8.7950159
Sum187.33018
Variance0.018063479
MonotonicityNot monotonic
2025-06-11T06:15:17.467976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1666666667 21
 
0.7%
0.3333333333 21
 
0.7%
0.02777777778 20
 
0.7%
0.09090909091 19
 
0.6%
0.0625 17
 
0.6%
0.1333333333 16
 
0.5%
0.03571428571 15
 
0.5%
0.02380952381 15
 
0.5%
0.25 15
 
0.5%
0.4 15
 
0.5%
Other values (1338) 2792
94.1%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
2 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.5 3
 
0.1%
1 14
0.5%
0.8333333333 1
 
< 0.1%
0.75 1
 
< 0.1%
0.6666666667 12
0.4%
0.6487935657 1
 
< 0.1%
0.6 1
 
< 0.1%

qtd_returns
Real number (ℝ)

Skewed  Zeros 

Distinct214
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.123736
Minimum0
Maximum80995
Zeros1480
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:17.585812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39
95-th percentile100
Maximum80995
Range80995
Interquartile range (IQR)9

Descriptive statistics

Standard deviation1513.2542
Coefficient of variation (CV)24.358712
Kurtosis2762.7913
Mean62.123736
Median Absolute Deviation (MAD)1
Skewness51.77237
Sum184259
Variance2289938.2
MonotonicityNot monotonic
2025-06-11T06:15:17.714113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1480
49.9%
1 164
 
5.5%
2 147
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
6 78
 
2.6%
5 61
 
2.1%
12 51
 
1.7%
8 43
 
1.4%
7 43
 
1.4%
Other values (204) 705
23.8%
ValueCountFrequency (%)
0 1480
49.9%
1 164
 
5.5%
2 147
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
5 61
 
2.1%
6 78
 
2.6%
7 43
 
1.4%
8 43
 
1.4%
9 41
 
1.4%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3331 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

avg_basket_size
Real number (ℝ)

High correlation  Skewed 

Distinct1974
Distinct (%)66.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.62037
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:17.843122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44.055556
Q1103.30833
median172.125
Q3281.64423
95-th percentile599.7
Maximum40498.5
Range40497.5
Interquartile range (IQR)178.3359

Descriptive statistics

Standard deviation791.92693
Coefficient of variation (CV)3.1725253
Kurtosis2253.6299
Mean249.62037
Median Absolute Deviation (MAD)82.875
Skewness44.655852
Sum740374.01
Variance627148.26
MonotonicityNot monotonic
2025-06-11T06:15:17.966276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
86 9
 
0.3%
82 9
 
0.3%
73 9
 
0.3%
60 8
 
0.3%
163 8
 
0.3%
140 8
 
0.3%
88 8
 
0.3%
75 8
 
0.3%
Other values (1964) 2878
97.0%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct1010
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.171203
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2025-06-11T06:15:18.088078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4802632
Q110
median17.2
Q327.75
95-th percentile57
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.523678
Coefficient of variation (CV)0.88058723
Kurtosis27.65049
Mean22.171203
Median Absolute Deviation (MAD)8.2
Skewness3.4963329
Sum65759.788
Variance381.17401
MonotonicityNot monotonic
2025-06-11T06:15:18.204623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 54
 
1.8%
14 40
 
1.3%
11 38
 
1.3%
9 33
 
1.1%
18 33
 
1.1%
20 31
 
1.0%
1 31
 
1.0%
10 30
 
1.0%
16 29
 
1.0%
17 28
 
0.9%
Other values (1000) 2619
88.3%
ValueCountFrequency (%)
1 31
1.0%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

Interactions

2025-06-11T06:15:14.171448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-11T06:15:03.438695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-11T06:15:07.745824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-11T06:15:09.810986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-11T06:15:11.077585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-11T06:15:12.070369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-11T06:15:10.987065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-11T06:15:13.024821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-11T06:15:14.077052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-11T06:15:18.295108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygros_revenueinvoice_noqtd_returnsquantityrecence_days
avg_basket_size1.000-0.0790.1880.447-0.1230.0580.5750.3830.2120.383-0.098
avg_recency_days-0.0791.000-0.1220.0470.018-0.962-0.249-0.167-0.397-0.1670.108
avg_ticket0.188-0.1221.000-0.613-0.1300.0980.246-0.3780.190-0.3780.047
avg_unique_basket_size0.4470.047-0.6131.000-0.007-0.0410.2900.6990.0190.699-0.106
customer_id-0.1230.018-0.130-0.0071.000-0.008-0.0760.012-0.0640.012-0.000
frequency0.058-0.9620.098-0.041-0.0081.0000.1620.1020.3600.102-0.032
gros_revenue0.575-0.2490.2460.290-0.0760.1621.0000.7440.3730.744-0.415
invoice_no0.383-0.167-0.3780.6990.0120.1020.7441.0000.2431.000-0.435
qtd_returns0.212-0.3970.1900.019-0.0640.3600.3730.2431.0000.243-0.121
quantity0.383-0.167-0.3780.6990.0120.1020.7441.0000.2431.000-0.435
recence_days-0.0980.1080.047-0.106-0.000-0.032-0.415-0.435-0.121-0.4351.000

Missing values

2025-06-11T06:15:15.212360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-11T06:15:15.315746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgros_revenuerecence_daysinvoice_noquantityavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.0297.0297.018.15222235.5000000.48611140.050.9705888.735294
1130473232.5956.0171.0171.018.90403527.2500000.04878035.0154.44444419.000000
2125836705.382.0232.0232.028.90250023.1875000.04569950.0335.20000015.466667
313748948.2595.028.028.033.86607192.6666670.0179210.087.8000005.600000
415100876.00333.03.03.0292.0000008.6000000.13636422.026.6666671.000000
5152914623.3025.0102.0102.045.32647123.2000000.05444129.0150.1428577.285714
6146885630.877.0327.0327.017.21978618.3000000.073569399.0172.42857115.571429
7178095411.9116.061.061.088.71983635.7000000.03910641.0171.4166675.083333
81531160767.900.02379.02379.025.5434644.1444440.315508474.0419.71428626.142857
9160982005.6387.067.067.029.93477647.6666670.0243900.087.5714299.571429
customer_idgros_revenuerecence_daysinvoice_noquantityavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
5602177271060.2515.066.066.016.0643946.00.2857146.0645.00000066.0
561217232421.522.036.036.011.70888912.00.1538460.0101.50000018.0
561317468137.0010.05.05.027.4000004.00.4000000.058.0000002.5
562413596697.045.0166.0166.04.1990367.00.2500000.0203.00000083.0
5630148931237.859.073.073.016.9568492.00.6666670.0399.50000036.5
563412479473.2011.030.030.015.7733334.00.33333334.0382.00000030.0
565514126706.137.015.015.047.0753333.01.00000050.0169.3333335.0
5661135211092.391.0435.0435.02.5112414.50.3000000.0244.333333145.0
567115060301.848.0120.0120.02.5153331.02.0000000.065.50000030.0
569012558269.967.011.011.024.5418186.00.285714196.0196.00000011.0